(28th-October-2020)
• DNN has achieved great results - a large margin in performance ratio of existing methods - still room for performance improvement
• There was not a particularly big theoretical progress (now) - is pre-training necessary? - CNN has remained almost unchanged since the latter half of the 1980s - that it turned out "It can be done if you do it"
• Improvement in computer performance · It is unchanged from the old days that know-how to derive performance is necessary
• Learning with large-scale data by large-scale NN - I want to improve recognition performance → NN multilayered → excessive learning risk → increase learning data amount → calculation performance required
• Expectations for Representation / feature learning - semi-supervised / transfer / self-taught learning
Questions.
Design Restricted Boltzmann Machine (RBM) for specific domain model.
Explain Convolutional Neural Network (CNN).
Why Deep NN is getting popular than Shallow NN?
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